Managing data sets based on user activity

ABSTRACT

An approach for managing data set access based on data set relevance. The approach monitors data set access activities associated with a user. The approach detects access of a first data set by the user. The approach determines a group of data sets associated with the first data set based on a data set mapping associated with the user. The approach recalls one or more data sets of the group of data sets from a slower storage device to a faster storage device.

TECHNICAL FIELD

The present invention relates generally to managing data, andspecifically, to predictively restoring data based on associated dataaccess.

BACKGROUND

As the volume of available information greatly increases,correspondingly, the quantity of data sets available for computer useare also greatly increasing. Accordingly, based on data usage, data setsare stored on many different hierarchical storage devices which caninclude different devices with differing data access speeds. In somecircumstances, data sets that are infrequently accessed are placed ondevices with lower access speed, e.g., a tape drive, as a lower coststorage alternative. When requested, the data sets residing on theseslower devices can be swapped to a higher speed device before providingaccess.

For example, an International Business Machines (IBM) Corporation z/OSData Facility Storage Management Subsystem (DFSMS) automates themanagement of storage at the file level by using a management class. Themanagement class indicates to DFSMS how to manage files, one associatedattribute of managing files is an indication of when a file is migrated,based on access frequency, to a lower access speed device. For long terminfrequently used data sets, the data sets are migrated to tape, andwhen accessed again DFSMS relocates the data sets to the higher accessspeed device.

In practice, it costs several minutes if the data sets are migratedbetween a higher speed device and a lower speed device. Further, when adata set is accessed some related data sets may also be accessedsubsequently, resulting in an even greater delay as data sets aremigrated between a higher speed device and a lower speed device.

BRIEF SUMMARY

According to an embodiment of the present invention, acomputer-implemented method for managing data set access based on dataset relevance, the computer-implemented method comprising: monitoring,by one or more processors, data set access activities associated with auser; detecting, by the one or more processors, access of a first dataset by the user; determining, by the one or more processors, a group ofdata sets associated with the first data set based on a data set mappingassociated with the user; recalling, by the one or more processors, oneor more data sets of the group of data sets from a slower storage deviceto a faster storage device.

According to an embodiment of the present invention, a computer systemfor managing data set access based on data set relevance, the computersystem comprising: one or more computer processors; one or morenon-transitory computer readable storage media; and program instructionsstored on the one or more non-transitory computer readable storagemedia, the program instructions comprising: program instructions tomonitor data set access activities associated with a user; programinstructions to detect access of a first data set by the user; programinstructions to determine a group of data sets associated with the firstdata set based on a data set mapping associated with the user; programinstructions to recall one or more data sets of the group of data setsfrom a slower storage device to a faster storage device.

According to an embodiment of the present invention, a computer systemfor managing data set access based on data set relevance, the computersystem comprising: one or more computer processors; one or morenon-transitory computer readable storage media; and program instructionsstored on the one or more non-transitory computer readable storagemedia, the program instructions comprising: program instructions tomonitor data set access activities associated with a user; programinstructions to detect access of a first data set by the user; programinstructions to determine a group of data sets associated with the firstdata set based on a data set mapping associated with the user; programinstructions to recall one or more data sets of the group of data setsfrom a slower storage device to a faster storage device.

Other aspects and embodiments of the present invention will becomeapparent from the following detailed description, which, when taken inconjunction with the drawings, illustrate by way of example theprinciples of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a cloud computing environment, according to embodimentsof the present invention.

FIG. 2 depicts abstraction model layers, according to embodiments of thepresent invention.

FIG. 3 is a high-level architecture, according to embodiments of thepresent invention.

FIG. 4 is an exemplary detailed architecture, according to embodimentsof the present invention.

FIG. 5 is a flowchart of a method, according to embodiments of thepresent invention.

FIG. 6 is a block diagram of internal and external components of a dataprocessing system in which embodiments described herein may beimplemented, according to embodiments of the present invention.

DETAILED DESCRIPTION

The following description is made for the purpose of illustrating thegeneral principles of the present invention and is not meant to limitthe inventive concepts claimed herein. Further, particular featuresdescribed herein can be used in combination with other describedfeatures in each of the various possible combinations and permutations.

Unless otherwise specifically defined herein, all terms are to be giventheir broadest possible interpretation including meanings implied fromthe specification as well as meanings understood by those skilled in theart and/or as defined in dictionaries, treatises, etc.

It must also be noted that, as used in the specification and theappended claims, the singular forms “a,” “an” and “the” include pluralreferents unless otherwise specified. It will be further understood thatthe terms “comprises” and/or “comprising,” when used in thisspecification, specify the presence of stated features, integers, steps,operations, elements, and/or components, but do not preclude thepresence or addition of one or more other features, integers, steps,operations, elements, components, and/or groups thereof.

The following description discloses several embodiments for predictivelyrestoring data based on associated data access. The embodiments describea mechanism which can manage multiple-level storage data sets based ontheir access relevance. The embodiments can create Related Data SetsGroup (RDSG) maps to record the related data sets usage for each type ofrole and user activity. The embodiments can monitor the data usage forusers of different roles, then can discover and predict the highly useddata sets. If the data sets are on secondary level devices and cannot beaccessed directly, the embodiments can prepare the data sets for access.After logon, the embodiments can identify users' different activitiesand monitor different data sets usage of each type of activity. Theembodiments can calculate the effect of the access of one data set onthe usage of the other data set, predict the potential data setsrequirement for each user activity. The embodiments can, based on theuser activity, prepare the predicted data sets prior to a need for theiruse.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based email). Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 1 , illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 1 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2 , a set of functional abstraction layersprovided by cloud computing environment 50 (FIG. 1 ) is shown. It shouldbe understood in advance that the components, layers, and functionsshown in FIG. 2 are intended to be illustrative only and embodiments ofthe invention are not limited thereto. As depicted, the following layersand corresponding functions are provided:

Hardware and software layer 60 include hardware and software components.Examples of hardware components include mainframes 61; RISC (ReducedInstruction Set Computer) architecture-based servers 62; servers 63;blade servers 64; storage devices 65; and networks and networkingcomponents 66. In some embodiments, software components include networkapplication server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and predictive data access management 96.

It should be noted that the embodiments of the present invention mayoperate with a user's permission. Any data may be gathered, stored,analyzed, etc., with a user's consent. In various configurations, atleast some of the embodiments of the present invention are implementedinto an opt-in application, plug-in, etc., as would be understood by onehaving ordinary skill in the art upon reading the present disclosure.

FIG. 3 is a high-level architecture for performing various operations ofFIG. 5 , in accordance with various embodiments. The architecture 300may be implemented in accordance with the present invention in any ofthe environments depicted in FIGS. 1-4 , among others, in variousembodiments. Of course, more or less elements than those specificallydescribed in FIG. 3 may be included in architecture 300, as would beunderstood by one of ordinary skill in the art upon reading the presentdescriptions.

Each of the steps of the method 500 (described in further detail below)may be performed by any suitable component of the architecture 300. Aprocessor, e.g., processing circuit(s), chip(s), and/or module(s)implemented in hardware and/or software, and preferably having at leastone hardware component may be utilized in any device to perform one ormore steps of the method 500 in the architecture 300. Illustrativeprocessors include, but are not limited to, a central processing unit(CPU), an application specific integrated circuit (ASIC), a fieldprogrammable gate array (FPGA), etc., combinations thereof, or any othersuitable computing device known in the art.

Architecture 300 includes a block diagram, showing a code updaterecommendation system, to which the invention principles may be applied.The architecture 300 comprises a client computer 302, a predictive dataaccess component 308 operational on a server computer 304 and a network306 supporting communication between the client computer 302 and theserver computer 304.

Client computer 302 can be any computing device on which software isinstalled for which an update is desired or required. Client computer302 can be a standalone computing device, management server, a webserver, a mobile computing device, or any other electronic device orcomputing system capable of receiving, sending, and processing data. Inother embodiments, client computer 302 can represent a server computingsystem utilizing multiple computers as a server system. In anotherembodiment, client computer 302 can be a laptop computer, a tabletcomputer, a netbook computer, a personal computer, a desktop computer orany programmable electronic device capable of communicating with othercomputing devices (not shown) within user persona generation environmentvia network 306.

In another embodiment, client computer 302 represents a computing systemutilizing clustered computers and components (e.g., database servercomputers, application server computers, etc.) that act as a single poolof seamless resources when accessed within install-time validationenvironment of architecture 300. Client computer 302 can includeinternal and external hardware components, as depicted and described infurther detail with respect to FIG. 5 .

Server computer 304 can be a standalone computing device, managementserver, a web server, a mobile computing device, or any other electronicdevice or computing system capable of receiving, sending, and processingdata. In other embodiments, server computer 304 can represent a servercomputing system utilizing multiple computers as a server system. Inanother embodiment, server computer 304 can be a laptop computer, atablet computer, a netbook computer, a personal computer, a desktopcomputer, or any programmable electronic device capable of communicatingwith other computing devices (not shown) within install-time validationenvironment of architecture 300 via network 306.

Network 306 can be, for example, a local area network (LAN), a wide areanetwork (WAN) such as the Internet, or a combination of the two, and caninclude wired, wireless, or fiber optic connections. In general, network306 can be any combination of connections and protocols that willsupport communications between client computer 302 and server computer304.

In one aspect of an embodiment of the present invention, predictive dataaccess component 308, operational on server computer 304, can providethe capability to identify a user's role based on the user's attributes.In another aspect of an embodiment, it should be noted that differenttypes of users can use different logon procedures. Accordingly, a userrole can be identified based on the type of user login.

In another aspect of an embodiment of the present invention, predictivedata access component 308 can obtain the RDSG data sets of theidentified type of role, then, if any data set is accessed, predictivedata access component 308 can collect information, e.g., role type, dataset name, etc. In another aspect of an embodiment of the presentinvention, predictive data access component 308 can calculate predictedrelated data sets of the currently accessed data, determine if thepredicted related data sets are available, and prepare the predictedrelated data sets for access, if they are currently not available.

In another aspect of an embodiment of the present invention, predictivedata access component 308 can monitor a user's different activities andthe data sets accessed by the user. In another aspect of an embodimentof the present invention, predictive data access component 308 candetect a user activity, then, if this is a first request, initiate andconfigure an RDSG map for the first time and collect the related datasets access information, e.g., user identity, data set name, accesstime, etc. In another aspect of an embodiment of the present invention,predictive data access component 308 can update the RDSG map as the datasets are accessed.

In another aspect of an embodiment of the present invention, predictivedata access component 308 can predict related data sets associated withthe present data access. It should be noted that if the predicted datasets are not available, predictive data access component 308 can sendrequests to a Hierarchical Storage Manager, prepare the data sets, andcan have the data sets loaded for expected access before required by anapplication.

FIG. 4 is an exemplary detailed architecture for performing variousoperations of FIG. 5 , in accordance with various embodiments. Thearchitecture 400 may be implemented in accordance with the presentinvention in any of the environments depicted in FIGS. 1-3 and 5 , amongothers, in various embodiments. Of course, more or less elements thanthose specifically described in FIG. 4 may be included in architecture400, as would be understood by one of skill in the art upon reading thepresent descriptions.

Each of the steps of the method 500 (described in further detail below)may be performed by any suitable component of the architecture 400. Aprocessor, e.g., processing circuit(s), chip(s), and/or module(s)implemented in hardware and/or software, and preferably having at leastone hardware component, may be utilized in any device to perform one ormore steps of the method 500 in the architecture 400. Illustrativeprocessors include, but are not limited to, a central processing unit(CPU), an application specific integrated circuit (ASIC), a fieldprogrammable gate array (FPGA), etc., combinations thereof, or any othersuitable computing device known in the art.

Architecture 400 provides a detailed view of at least some of themodules of architecture 300. Architecture 400 can comprise a predictivedata access component 308, which can further comprise detectioncomponent 402, check component 404, record component 406 and calculatecomponent 408.

In one aspect of an embodiment of the present invention, detectioncomponent 402 can monitor user data set access requests and operatingactivities. In another aspect of an embodiment, detection component 402can send attributes such as, but not limited to, a user identification,a data set name and a time stamp associated with a request to recordcomponent 406 (described subsequently).

In one aspect of an embodiment of the present invention, check component404 can monitor role-based data set access requests based on a userlogin. In another aspect of an embodiment of the present invention,check component 404 can collect attributes such as, but not limited to,data set access times and roles associated with a user, sending thecollected information to record component 406 (described subsequently).

In one aspect of an embodiment of the present invention, recordcomponent 406 can receive the data set access information sent fromdetection component 402 and check component 404. It should be noted thatthe types of activities considered for the data sets can compriseactivities such as, but not limited to, logon, monitor, debug, etc. andcan be accessed as related data sets.

In another aspect of an embodiment of the present invention, recordcomponent 406 can select profiles and component related working datasets of activities as an RDSG. It should be noted that a user can defineother desired data sets into an RDSG. In another aspect of an embodimentof the present invention, record component 406 can analyze an accesseddata set and determine an access count for associated data sets within apredetermined time interval. In another aspect of an embodiment of thepresent invention, record component 406 can maintain, for the associateddata sets, an RDSG map for the types of activities, recording the datasets access count and frequency.

In another aspect of an embodiment of the present invention, calculatecomponent 408 can provide the capability to calculate the effect of theaccess of one data set on the access of another data set, e.g., acorrelation ratio (CR) between a first data set (DS1) and a second dataset (DS2) based on an access count of the first data set (AC1) and anaccess count (AC2_(T)) of the second data set within a predeterminedtime interval (CR=AC1/AC2_(T)).

In another aspect of an embodiment of the present invention, calculatecomponent 408 can predict the potential data set requirements based onuser activity, constrained by a predetermined threshold, and provide thedata set prediction results. It should be noted that if one or more ofthe predicted data sets are not available, then calculate component 408can send a request to an associated Hierarchical Storage Manager (HSM)to restore the one or more data sets.

FIG. 5 is an exemplary flowchart of a method 500 for managing data setaccess based on data set relevance. At step 502, an embodiment canmonitor, via check component 404, data set access activities associatedwith a user. At step 504, the embodiment can detect, via detectioncomponent 402, access of a first data set by a user. At step 506, theembodiment can determine, via record component 406, a group of data setsassociated with the first data set based on a data set mappingassociated with the user. At step 508, the embodiment can recall, viacalculate component 408, the one or more data sets of the group of datasets from a slower storage device to a faster storage device.

FIG. 6 depicts computer system 600, an example computer systemrepresentative of client computer 302 and server computer 304. Computersystem 600 includes communications fabric 602, which providescommunications between computer processor(s) 604, memory 606, persistentstorage 608, communications unit 610, and input/output (I/O)interface(s) 612. Communications fabric 602 can be implemented with anyarchitecture designed for passing data and/or control informationbetween processors (such as microprocessors, communications and networkprocessors, etc.), system memory, peripheral devices, and any otherhardware components within a system. For example, communications fabric602 can be implemented with one or more buses.

Computer system 600 includes processors 604, cache 616, memory 606,persistent storage 608, communications unit 610, input/output (I/O)interface(s) 612 and communications fabric 602. Communications fabric602 provides communications between cache 616, memory 606, persistentstorage 608, communications unit 610, and input/output (I/O)interface(s) 612. Communications fabric 602 can be implemented with anyarchitecture designed for passing data and/or control informationbetween processors (such as microprocessors, communications and networkprocessors, etc.), system memory, peripheral devices, and any otherhardware components within a system. For example, communications fabric602 can be implemented with one or more buses or a crossbar switch.

Memory 606 and persistent storage 608 are computer readable storagemedia. In this embodiment, memory 606 includes random access memory(RAM). In general, memory 606 can include any suitable volatile ornon-volatile computer readable storage media. Cache 616 is a fast memorythat enhances the performance of processors 604 by holding recentlyaccessed data, and data near recently accessed data, from memory 606.

Program instructions and data used to practice embodiments of thepresent invention may be stored in persistent storage 608 and in memory606 for execution by one or more of the respective processors 604 viacache 616. In an embodiment, persistent storage 608 includes a magnetichard disk drive. Alternatively, or in addition to a magnetic hard diskdrive, persistent storage 608 can include a solid state hard drive, asemiconductor storage device, read-only memory (ROM), erasableprogrammable read-only memory (EPROM), flash memory, or any othercomputer readable storage media that is capable of storing programinstructions or digital information.

The media used by persistent storage 608 may also be removable. Forexample, a removable hard drive may be used for persistent storage 608.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of persistent storage608.

Communications unit 610, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 610 includes one or more network interface cards.Communications unit 610 may provide communications through the use ofeither or both physical and wireless communications links. Programinstructions and data used to practice embodiments of the presentinvention may be downloaded to persistent storage 608 throughcommunications unit 610.

I/O interface(s) 612 allows for input and output of data with otherdevices that may be connected to each computer system. For example, I/Ointerface 612 may provide a connection to external devices 618 such as akeyboard, keypad, a touch screen, and/or some other suitable in-putdevice. External devices 618 can also include portable computer readablestorage media such as, for example, thumb drives, portable optical ormagnetic disks, and memory cards. Software and data used to practiceembodiments of the present invention can be stored on such portablecomputer readable storage media and can be loaded onto persistentstorage 608 via I/O interface(s) 612. I/O interface(s) 612 also connectto display 620.

Display 620 provides a mechanism to display data to a user and may be,for example, a computer monitor.

The components described herein are identified based upon theapplication for which they are implemented in a specific embodiment ofthe invention. However, it should be appreciated that any particularcomponent nomenclature herein is used merely for convenience, and thusthe invention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a computer, or other programmable data processing apparatusto produce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks. These computerreadable program instructions may also be stored in a computer readablestorage medium that can direct a computer, a programmable dataprocessing apparatus, and/or other devices to function in a particularmanner, such that the computer readable storage medium havinginstructions stored therein comprises an article of manufactureincluding instructions which implement aspects of the function/actspecified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be accomplished as one step, executed concurrently,substantially concurrently, in a partially or wholly temporallyoverlapping manner, or the blocks may sometimes be executed in thereverse order, depending upon the functionality involved. It will alsobe noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

Moreover, a system according to various embodiments may include aprocessor and logic integrated with and/or executable by the processor,the logic being configured to perform one or more of the process stepsrecited herein. By integrated with, what is meant is that the processorhas logic embedded therewith as hardware logic, such as an applicationspecific integrated circuit (ASIC), a FPGA, etc. By executable by theprocessor, what is meant is that the logic is hardware logic; softwarelogic such as firmware, part of an operating system, part of anapplication program; etc., or some combination of hardware and softwarelogic that is accessible by the processor and configured to cause theprocessor to perform some functionality upon execution by the processor.Software logic may be stored on local and/or remote memory of any memorytype, as known in the art. Any processor known in the art may be used,such as a software processor module and/or a hardware processor such asan ASIC, a FPGA, a central processing unit (CPU), an integrated circuit(IC), a graphics processing unit (GPU), etc.

It will be clear that the various features of the foregoing systemsand/or methodologies may be combined in any way, creating a plurality ofcombinations from the descriptions presented above.

It will be further appreciated that embodiments of the present inventionmay be provided in the form of a service deployed on behalf of acustomer to offer service on demand.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration but are not intended tobe exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A computer-implemented method for managing dataset access based on data set relevance, the computer-implemented methodcomprising: monitoring, by one or more processors, data set accessactivities associated with a user; detecting, by the one or moreprocessors, access of a first data set by the user; determining, by theone or more processors, a group of data sets associated with the firstdata set based on a data set mapping associated with the user; andrecalling, by the one or more processors, one or more data sets of thegroup of data sets from a slower storage device to a faster storagedevice.
 2. The computer-implemented method of claim 1, furthercomprising: receiving, by the one or more processors, informationassociated with a login by the user; identifying, by the one or moreprocessors, a role associated with the login based on the information;predicting, by the one or more processors, the group of data setsrequired by the user based on the role; and generating, by the one ormore processors, the data set mapping based on the predicting.
 3. Thecomputer-implemented method of claim 2, wherein the data set mapping isupdated based on not detecting the first data set in the mapping.
 4. Thecomputer-implemented method of claim 1, wherein data sets included inthe data set mapping are based on a correlation ratio (CR) between adata set one (DS1) and a data set two (DS2) of an access count of thefirst data set (AC1) and an access count (AC2_(T)) of a second data setwithin a predetermined time interval (CR=AC1/AC2_(T)).
 5. Thecomputer-implemented method of claim 1, wherein the access activitiescomprise a user identity, a data set name, and a data set request time.6. The computer-implemented method of claim 2, wherein the informationcomprises a user role and a data set access time.
 7. Thecomputer-implemented method of claim 4, wherein the data sets areincluded if the correlation ratio is greater than a predeterminedthreshold.
 8. A computer program product for managing data set accessbased on data set relevance, the computer program product comprising:one or more non-transitory computer readable storage media and programinstructions stored on the one or more non-transitory computer readablestorage media, the program instructions comprising: program instructionsto monitor data set access activities associated with a user; programinstructions to detect access of a first data set by the user; programinstructions to determine a group of data sets associated with the firstdata set based on a data set mapping associated with the user; andprogram instructions to recall one or more data sets of the group ofdata sets from a slower storage device to a faster storage device. 9.The computer program product of claim 8, further comprising: receiving,by the one or more processors, information associated with a login bythe user; identifying, by the one or more processors, a role associatedwith the login based on the information; predicting, by the one or moreprocessors, the group of data sets required by the user based on therole; and generating, by the one or more processors, the data setmapping based on the predicting.
 10. The computer program product ofclaim 9, wherein the data set mapping is updated based on not detectingthe first data set in the mapping.
 11. The computer program product ofclaim 8, wherein data sets included in the data set mapping are based ona correlation ratio (CR) between a data set one (DS1) and a data set two(DS2) of an access count of the first data set (AC1) and an access count(AC2_(T)) of a second data set within a predetermined time interval(CR=AC1/AC2_(T)).
 12. The computer program product of claim 8, whereinthe access activities comprise a user identity, a data set name, and adata set request time.
 13. The computer program product of claim 9,wherein the information comprises a user role and a data set accesstime.
 14. The computer program product of claim 11, wherein the datasets are included if the correlation ratio is greater than apredetermined threshold.
 15. A computer system for managing data setaccess based on data set relevance, the computer system comprising: oneor more computer processors; one or more non-transitory computerreadable storage media; and program instructions stored on the one ormore non-transitory computer readable storage media, the programinstructions comprising: program instructions to monitor data set accessactivities associated with a user; program instructions to detect accessof a first data set by the user; program instructions to determine agroup of data sets associated with the first data set based on a dataset mapping associated with the user; and program instructions to recallone or more data sets of the group of data sets from a slower storagedevice to a faster storage device.
 16. The computer system of claim 15,further comprising: receiving, by the one or more processors,information associated with a login by the user; identifying, by the oneor more processors, a role associated with the login based on theinformation; predicting, by the one or more processors, the group ofdata sets required by the user based on the role; and generating, by theone or more processors, the data set mapping based on the predicting.17. The computer system of claim 16, wherein the data set mapping isupdated based on not detecting the first data set in the mapping. 18.The computer system of claim 15, wherein data sets included in the dataset mapping are based on a correlation ratio (CR) between a data set one(DS1) and a data set two (DS2) of an access count of the first data set(AC1) and an access count (AC2_(T)) of a second data set within apredetermined time interval (CR=AC1/AC2_(T)) and wherein the data setsare included if the correlation ratio is greater than a predeterminedthreshold.
 19. The computer system of claim 15, wherein the accessactivities comprise a user identity, a data set name, and a data setrequest time.
 20. The computer system of claim 16, wherein theinformation comprises a user role and a data set access time.